A field experiment was conducted during winter season of 2021 at a research station of college of agricultural engineering sciences, university of Baghdad to determine the response of active fertility percentage and seed yield and its components of faba bean (Vicia faba L. cv. Aguadulce) to distance between plants and spraying of nano and traditional boron. A Randomized Complete Block Design according to split-plots arrangement was used at three replicates. The main plots were three distances between plants (25, 35 and 45 cm), while the sub plots including spraying of distilled water only (control treatment), spraying of boron at a 100 mg L-1 and spraying of nano boron at two concentrations (10 and 15 mg L-1). The results showed that the 25 cm distance between plants was significantly superiority and gave a highest mean of seed yield (4.968 ton ha-1), whereas the 45 cm distance between plants was significantly superiority and gave highest means of number of branches (10.83 branch plant-1), number of flowers (400.4 flower plant-1), number of pods (28.36 pod plant-1), active fertility percentage (7.10%) and umber of seeds (6.66 seed pod-1). The spraying of nano boron at a 10 mg L-1 was significantly superior and gave the highest means of number of pods (26.91 pod plant-1), active fertility percentage (7.01%), number of seeds (6.23 seed pod-1) and seed yield (4.334 ton ha-1), while the spraying of nano boron at a 15 mg L-1 was significantly superior and gave the highest means of number of branches (9.83 branch plant-1) and number of flowers (400.0 flower plant-1). The interaction between two factors had significant effect on the most studied traits.
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Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the
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This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.
In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.
The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi
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Transient three-dimensional natural convection heat transfer due to the influences of heating from one side of an enclosure filled with a saturated porous media, whereas the opposite side is maintained at a constant cold temperature, and the other four sides are adiabatic, were investigated in the present work experimentally. Silica sand was used as a porous media saturated with distilled water filled in a cubic enclosure heated from the side,using six electrical controlled heaters, at constant temperatures of (60, 70, 80, 90, and 100oC). The inverse side cooled at a constant temperature of (24oC) using an aluminum heat exchanger, consisted of 15 channels feeded with constant temperature water. Eighty thermocouples were used to control t
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
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